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From: Michael Roberts Blog <[log in to unmask]>
Date: Sat, Apr 8, 2023 at 2:06 PM
Subject: [New post] AI-GPT: a game changer?


[image: Site logo image] michael roberts posted: " ChatGPT is being
heralded as a revolution in ‘artificial intelligence’ (AI) and has been
taking the media and tech world by storm since launching in late 2022.
According to OpenAI, ChatGPT is "an artificial intelligence trained to
assist with a vari" Michael Roberts Blog
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AI-GPT:
a game changer?
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michael roberts

Apr 8

ChatGPT is being heralded as a revolution in ‘artificial intelligence’ (AI)
and has been taking the media and tech world by storm since launching in
late 2022.

According to OpenAI <https://openai.com/blog/chatgpt/>, ChatGPT is *"an
artificial intelligence trained to assist with a variety of tasks."* More
specifically, it is a large language model (LLM) designed to produce
human-like text and converse with people, hence the "Chat" in ChatGPT.

GPT stands for Generative Pre-trained Transformer.  The GPT models are
pre-trained by human developers and then are left to learn for themselves
and generate ever increasing amounts of knowledge, delivering that
knowledge in an acceptable way to humans (chat).

Practically, this means you present the model with a query or request by
entering it into a text box. The AI then processes this request and
responds based on the information that it has available. It can do many
tasks, from holding a conversation to writing an entire exam paper; from
making a brand logo to composing music and more.  So much more than a
simple Google-type search engine or Wikipedia, it is claimed.

Human developers are working to raise the ‘intelligence’ of GPTs.  The
current version of GPT is 3.5 with 4.0 coming out by the end of this year.
And it is rumoured that ChatGPT-5 could achieve ‘artificial general
intelligence’ (AGI). This means it could pass the Turing test,
<https://en.wikipedia.org/wiki/Turing_test>which is a test that determines
if a computer can communicate in a manner that is indistinguishable from a
human.

Will LLMs be a game changer for capitalism in this decade?  Will these
self-learning machines be able to increase the productivity of labour at an
unprecedented rate and so take the major economies out of their current
‘long depression’ of low real GDP, investment and income growth; and then
enable the world to take new strides out of poverty?  This is the claim by
some of the ‘techno-optimists’ that occupy the media.

Let’s consider the answers to those questions.

First, just how good and accurate are the current versions of ChatGPT?
Well, not very, just yet.  There are plenty of “facts” about the world
which humans disagree on. Regular search lets you compare those versions
and consider their sources. A language model might instead attempt to
calculate some kind of average of every opinion it’s been trained on—which
is sometimes what you want, but often is not. ChatGPT sometimes writes
plausible-sounding but incorrect or nonsensical answers.  Let me give you
some examples.

I asked ChatGPT 3.5: who is Michael Roberts, Marxist economist?  This was
the reply.
<https://public-api.wordpress.com/bar/?stat=groovemails-events&bin=wpcom_email_click&redirect_to=https%3A%2F%2Fthenextrecession.files.wordpress.com%2F2023%2F04%2Fgpt1.png&sr=1&signature=c5d458b3a459cc0a4f46683541ae498b&user=155152313&_e=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&_z=z>

This is mostly right but it is also wrong in parts (I won’t say which).

Then I asked it to review my book, The Long Depression.  This is what it
said:
<https://public-api.wordpress.com/bar/?stat=groovemails-events&bin=wpcom_email_click&redirect_to=https%3A%2F%2Fthenextrecession.files.wordpress.com%2F2023%2F04%2Fgpt2.png&sr=1&signature=0b385318e2b257dd3a445e4a55cd6276&user=155152313&_e=eyJlcnJvciI6bnVsbCwiYmxvZ19pZCI6MTEyNTY4NzQsImJsb2dfbGFuZyI6ImVuIiwic2l0ZV9pZF9sYWJlbCI6IndwY29tIiwiaGFzX2ZlYXR1cmVkX2ltYWdlIjoiMCIsIl91aSI6MTU1MTUyMzEzLCJsb2NhbGUiOiJlbiIsImN1cnJlbmN5IjoiVVNEIiwiY291bnRyeV9jb2RlX3NpZ251cCI6IlVTIiwic2lnbnVwX2Zsb3dfbmFtZSI6ImxvZ2luIiwiZW1haWxfZG9tYWluIjoiZ21haWwuY29tIiwicG9zdF9pZCI6MjM4NjQsImRhdGVfc2VudCI6IjIwMjMtMDQtMDgiLCJlbWFpbF9pZCI6ImI5ZTZkZjJkM2JmZDk5MmJiZTE1OWU2MTJhOWY5MDdiIiwiZW1haWxfbmFtZSI6Im5ldy1wb3N0IiwidGVtcGxhdGUiOiJuZXctcG9zdCIsImxpbmtfZGVzYyI6InBvc3QtdXJsIiwiYW5jaG9yX3RleHQiOiIiLCJfZHIiOm51bGwsIl9kbCI6Ilwvd3BcL3YyXC9zaXRlc1wvMTEyNTY4NzRcL3Bvc3RzXC8yMzg2ND9fZW52ZWxvcGU9MSZlbnZpcm9ubWVudC1pZD1wcm9kdWN0aW9uJl9ndXRlbmJlcmdfbm9uY2U9Yzc0YzM3YzgzZSZfbG9jYWxlPXVzZXIiLCJfdXQiOiJ3cGNvbTp1c2VyX2lkIiwiX3VsIjoicGhpbGdhc3BlcmMwMTM3YjE0YzQiLCJfZW4iOiJ3cGNvbV9lbWFpbF9jbGljayIsIl90cyI6MTY4MDk4MDgwMDkzMCwiYnJvd3Nlcl90eXBlIjoicGhwLWFnZW50IiwiX2F1YSI6IndwY29tLXRyYWNrcy1jbGllbnQtdjAuMyIsImJsb2dfdHoiOiIwIiwidXNlcl9sYW5nIjoiZW4ifQ=&_z=z>

This gives a very ‘general’ review or synopsis of my book, but leaves out
the kernel of the book’s thesis: the role of profitability in crises under
capitalism.  Why, I don’t know.

So I asked this question about Marx’s law of profitability:
<https://public-api.wordpress.com/bar/?stat=groovemails-events&bin=wpcom_email_click&redirect_to=https%3A%2F%2Fthenextrecession.files.wordpress.com%2F2023%2F04%2Fgpt3.png&sr=1&signature=25fb2aab1f81660ce40a1095d2e50633&user=155152313&_e=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&_z=z>

Again, this is broadly right – but just broadly.  The answer does not
really take you very far in understanding the law.  Indeed, it is no better
than Wikipedia.  Of course, you can dig (prompt) further to get more
detailed answers. But there seems to be some way to go in replacing human
research and analysis.

Then there is the question of the productivity of labour and jobs. Goldman
Sachs economists reckon that if the technology lived up to its promise, it
would bring “significant disruption” to the labour market, exposing the
equivalent of 300m full-time workers across the major economies to
automation of their jobs. Lawyers and administrative staff would be among
those at greatest risk of becoming redundant (and probably economists).
They calculate that roughly two-thirds of jobs in the US and Europe are
exposed to some degree of AI automation, based on data on the tasks
typically performed in thousands of occupations.

Most people would see less than half of their workload automated and would
probably continue in their jobs, with some of their time freed up for more
productive activities. In the US, this would apply to 63% of the workforce,
they calculated. A further 30% working in physical or outdoor jobs would be
unaffected, although their work might be susceptible to other forms of
automation.
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The GS economists concluded: *“Our findings reveal that around 80% of the
US workforce could have at least 10% of their work tasks affected by the
introduction of LLMs, while approximately 19% of workers may see at least
50% of their tasks impacted.”*

With access to an LLM, about 15% of all worker tasks in the US could be
completed significantly faster at the same level of quality. When
incorporating software and tooling built on top of LLMs, this share
increases to 47-56% of all tasks.  About 7% of US workers are in jobs where
at least half of their tasks could be done by generative AI and are
vulnerable to replacement. At a global level, since manual jobs are a
bigger share of employment in the developing world, GS estimates about a
fifth of work could be done by AI — or about 300m full-time jobs across big
economies.

These job loss forecasts are nothing new.   In previous posts
<https://public-api.wordpress.com/bar/?stat=groovemails-events&bin=wpcom_email_click&redirect_to=https%3A%2F%2Fthenextrecession.wordpress.com%2F2015%2F09%2F24%2Frobots-and-ai-utopia-or-dystopia-part-three%2F&sr=1&signature=0a8f5826c217579552a005bfe02b0ba4&user=155152313&_e=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&_z=z>,
I have outlined several forecasts on the number of jobs that will be lost
to robots and AI over the next decade or more.  It appears to be huge; and
not just in manual work in factories but also in so-called white-collar
work.

It is in the essence of capitalist accumulation that the workers will
continually face the loss of their work from capitalist investment in
machines.  The replacement of human labour by machines started at the
beginning of the British Industrial Revolution in the textile industry, and
automation played a major role in American industrialization during the
19th century. The rapid mechanization of agriculture starting in the middle
of the 19th century is another example of automation.

As Engels explained, whereas mechanisation not only shed jobs, often it
also created new jobs in new sectors, as Engels noted in his book, The
condition of the working class in England (1844) – see my book on Engels’
economics pp54-57.
<https://www.lulu.com/shop/michael-roberts/engels-200/paperback/product-y9pzdr.html?page=1&pageSize=4>
But as Marx identified this in the 1850s: *“The real facts, which are
travestied by the optimism of the economists, are these: the workers, when
driven out of the workshop by the machinery, are thrown onto the
labour-market. Their presence in the labour-market increases the number of
labour-powers which are at the disposal of capitalist exploitation…the
effect of machinery, which has been represented as a compensation for the
working class, is, on the contrary, a most frightful scourge. …. As soon as
machinery has set free a part of the workers employed in a given branch of
industry, the reserve men are also diverted into new channels of employment
and become absorbed in other branches; meanwhile the original victims,
during the period of transition, for the most part starve and perish.”
*Grundrisse.
The implication here is that automation means increased precarious jobs and
rising inequality.

Up to now, mechanisation has still required human labour to start and
maintain it. But are we now moving towards the takeover of all tasks, and
especially those requiring complexity and ideas with LLMs? And will this
mean a dramatic rise in the productivity of labour so that capitalism will
have a new lease of life?

If LLMs can replace human labour and thus raise the rate of surplus value
dramatically, but without a sharp rise in investment costs of physical
machinery (what Marx called a rising organic composition of capital), then
perhaps the average profitability of capital will jump back from its
current lows.

Goldman Sachs claims that these “generative” AI systems such as ChatGPT
could spark a productivity boom that would eventually raise annual global
GDP by 7% over a decade.  If corporate investment in AI continued to grow
at a similar pace to software investment in the 1990s, US AI investment
alone could approach 1% of US GDP by 2030.
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I won’t go into how GS calculates these outcomes, because the results are
conjectures.  But even if we accept the results, are they such an
exponential leap?  According to the latest forecasts by the World Bank,
<https://openknowledge.worldbank.org/server/api/core/bitstreams/6cadf98e-e265-4055-aef7-fad9943a0afd/content>
global growth is set to decline by roughly a third from the rate that
prevailed in the first decade of this century—to just 2.2% a year.  And the
IMF puts the average growth rate at 3% a year for the rest of this decade.

If we add in the GS forecast of the impact of LLMs, we get about 3.0-3.5% a
year for global real GDP growth, maybe – and this does not account for
population growth.  In other words, the likely impact would be no better
than the average seen since the 1990s.  That reminds us of what Economist
Robert Solow famously said in 1987 that the *“computer age was everywhere
except for the productivity statistics.”*
<https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/is-the-solow-paradox-back>

US economist Daren Acemoglu adds that not all automation technologies
actually raise the productivity of labour.  That’s because companies mainly
introduce automation in areas that may boost profitability, like marketing,
accounting or fossil fuel technology, but not raise productivity for the
economy as a whole or meet social needs. Big Tech has a particular approach
to business and technology that is centered on the use of algorithms for
replacing humans. It is no coincidence that companies such as Google are
employing less than one tenth of the number of workers that large
businesses, such as General Motors, used to do in the past. This is a
consequence of Big Tech’s business model, which is based not on creating
jobs but automating them.

That’s the business model for AI under capitalism.  But under cooperative
commonly owned automated means of production, there are many applications
of AI that instead could augment human capabilities and create new tasks in
education, health care, and even in manufacturing. Acemoglu suggested
that *“rather
than using AI for automated grading, homework help, and increasingly for
substitution of algorithms for teachers, we can invest in using AI for
developing more individualized, student-centric teaching methods that are
calibrated to the specific strengths and weaknesses of different groups of
pupils. Such technologies would lead to the employment of more teachers, as
well as increasing the demand for new teacher skills — thus exactly going
in the direction of creating new jobs centered on new tasks.”*  And rather
than reduce jobs and the livelihoods of humans, AI under common ownership
and planning could reduce the hours of human labour for all.

And then there is the issue of the profitability boost provided by AI
technology.  Even if LLM investment requires less physical means of
production and lowers costs of such capital, the loss of human labour power
could be even greater.  So Marx’s law of profitability would still apply.
It’s the great contradiction of capitalism that *increasing* the
productivity of labour through more machines (AI) *reduces* the
profitability of capital.  That leads to regular and recurring crises of
production, investment and employment – of increasing intensity and
duration.

Finally, there is the question of intelligence.  Microsoft argues that
intelligence is a *“very general mental capability that, among other
things, involves the ability to reason, plan, solve problems, think
abstractly, comprehend complex ideas, learn quickly and learn from
experience.” *Microsoft hints that LLMs could soon obtain this ‘generalised
intelligence’ and surpass all human ability to think.

But even here, there is scepticism. *“The ChatGPT model is huge, but it’s
not huge enough to retain every exact fact it’s encountered in its training
set.  It can produce a convincing answer to anything, but that doesn’t mean
it’s reflecting actual facts in its answers. You always have to stay
sceptical and fact check what it tells you. Language models are also famous
for “hallucinating”—for inventing new facts that fit the sentence structure
despite having no basis in the underlying data.”*  That’s not very
encouraging.

But Guglielmo Carchedi has a more fundamental reason to deny that AI can
replace human ‘intelligence’.  Carchedi and Roberts: *“machines behave
according only to the rules of formal logic.  Contrary to humans, machines
are structurally unable to behave according to the rules of dialectical
thinking. Only humans do that.”*  (Capitalism in the 21st century
<https://www.plutobooks.com/book/>, p167).  Here is the ChatGPT answer to
the dialectical question:  “*Can A be equal to A and at the same time be
different from A?”  "No, it is not possible for A to be equal to A and at
the same time be different from A. This would be a contradiction in terms,
as the statement "A is equal to A" is a tautology and always true, while
the statement "A is different from A" is a contradiction and always false.
Therefore, these two statements cannot both be true at the same time.”*

Machines cannot think of potential and qualitative changes.  New knowledge
comes from such transformations (human), not from the extension of existing
knowledge (machines).  Only human intelligence is social and can see the
potential for change, in particular social change, that leads to a better
life for humanity and nature.
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